activity
20192026
most citedBig Code != Big Vocabulary: Open-Vocabulary Models for Source Code

143 citations · 179 across the 11 of their papers we have counts for

collaborators

13 papers

cs.SE2026

Architectural Degradation: How to Measure and to Remediate

Noman Ahmad, Ruoyu Su, Matteo Esposito +3

Context. Architectural degradation undermines software maintainability, evolvability, and quality. However, existing research remains fragmented across measurement approaches, metr…

cs.SE2023

One Microservice per Developer: Is This the Trend in OSS?

Dario Amoroso d'Aragona, Xiaoxhou Li, Tomas Cerny +3

When developing and managing microservice systems, practitioners suggest that each microservice should be owned by a particular team. In effect, there is only one team with the res…

cs.SE2023★ 2 cited

On the Empirical Evidence of Microservice Logical Coupling. A Registered Report

Dario Amoroso d Aragona, Luca Pascarella, Andrea Janes +3

[Context] Coupling is a widely discussed metric by software engineers while developing complex software systems, often referred to as a crucial factor and symptom of a poor or good…

cs.SE2023

Breaks and Code Quality: Investigating the Impact of Forgetting on Software Development. A Registered Report

Dario Amoroso d'Aragona, Luca Pascarella, Andrea Janes +3

Developers interrupting their participation in a project might slowly forget critical information about the code, such as its intended purpose, structure, the impact of external de…

cs.SE2023★ 3 cited

Early Career Developers' Perceptions of Code Understandability. A Study of Complexity Metrics

Matteo Esposito, Andrea Janes, Terhi Kilamo +1

Context. Code understandability is fundamental. Developers need to understand the code they are modifying clearly. A low understandability can increase the amount of coding effort,…

eess.SP2023

Lowering Detection in Sport Climbing Based on Orientation of the Sensor Enhanced Quickdraw

Sadaf Moaveninejad, Andrea Janes, Camillo Porcaro

Tracking climbers' activity to improve services and make the best use of their infrastructure is a concern for climbing gyms. Each climbing session must be analyzed from beginning…

eess.SP2022★ 1 cited

Climbing Routes Clustering Using Energy-Efficient Accelerometers Attached to the Quickdraws

Sadaf Moaveninejad, Andrea Janes, Camillo Porcaro +3

One of the challenges for climbing gyms is to find out popular routes for the climbers to improve their services and optimally use their infrastructure. This problem must be addres…

cs.SE2022

Open Tracing Tools: Overview and Critical Comparison

Andrea Janes, Xiaozhou Li, Valentina Lenarduzzi

Background. Coping with the rapid growing complexity in contemporary software architecture, tracing has become an increasingly critical practice and been adopted widely by software…

cs.SE2022

CATTO: Just-in-time Test Case Selection and Execution

Dario Amoroso d'Aragona, Fabiano Pecorelli, Simone Romano +4

Regression testing ensures a System Under Test (SUT) still works as expected after changes to it. The simplest approach for regression testing consists of re-running the entire tes…

cs.SE2021

Mining Software Repositories with a Collaborative Heuristic Repository

Hlib Babii, Julian Aron Prenner, Laurin Stricker +3

Many software engineering studies or tasks rely on categorizing software engineering artifacts. In practice, this is done either by defining simple but often imprecise heuristics,…

cs.CR2020★ 5 cited

Improving Predictability of User-Affecting Metrics to Support Anomaly Detection in Cloud Services

Vilc Rufino, Mateus Nogueira, Alberto Avritzer +7

Anomaly detection systems aim to detect and report attacks or unexpected behavior in networked systems. Previous work has shown that anomalies have an impact on system performance,…

cs.SE2020★ 143 cited

Big Code != Big Vocabulary: Open-Vocabulary Models for Source Code

Rafael-Michael Karampatsis, Hlib Babii, Romain Robbes +2

Statistical language modeling techniques have successfully been applied to large source code corpora, yielding a variety of new software development tools, such as tools for code s…

cs.CL2019★ 25 cited

Modeling Vocabulary for Big Code Machine Learning

Hlib Babii, Andrea Janes, Romain Robbes

When building machine learning models that operate on source code, several decisions have to be made to model source-code vocabulary. These decisions can have a large impact: some…